Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ IEICE Transactions o...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
IEICE Transactions on Communications
Article . 2010 . Peer-reviewed
Data sources: Crossref
DBLP
Article . 2010
Data sources: DBLP
versions View all 3 versions
addClaim

Design and Implementation of High Interaction Client Honeypot for Drive-by-Download Attacks

Authors: AKIYAMA, Mitsuaki; IWAMURA, Makoto; KAWAKOYA, Yuhei; AOKI, Kazufumi; ITOH, Mitsutaka;

Design and Implementation of High Interaction Client Honeypot for Drive-by-Download Attacks

Abstract

Nowadays, the number of web-browser targeted attacks that lead users to adversaries' web sites and exploit web browser vulnerabilities is increasing, and a clarification of their methods and countermeasures is urgently needed. In this paper, we introduce the design and implementation of a new client honeypot for drive-by-download attacks that has the capacity to detect and investigate a variety of malicious web sites. On the basis of the problems of existing client honeypots, we enumerate the requirements of a client honeypot: 1) detection accuracy and variety, 2) collection variety, 3) performance efficiency, and 4) safety and stability. We improve our system with regard to these requirements. The key features of our developed system are stepwise detection focusing on exploit phases, multiple crawler processing, tracking of malware distribution networks, and malware infection prevention. Our evaluation of our developed system in a laboratory experiment and field experiment indicated that its detection variety and crawling performance are higher than those of existing client honeypots. In addition, our system is able to collect information for countermeasures and is secure and stable for continuous operation. We conclude that our system can investigate malicious web sites comprehensively and support countermeasures.

Related Organizations
Keywords

client honeypot, malware, intrusion detection

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    44
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
44
Top 10%
Top 1%
Top 10%